Association rules generated from mining data at multiple levels of abstraction are called multiple-level or multilevel association rules.

• Multilevel association rules can be mined efficiently using concept hierarchies under a support-confidence framework.
• Rules at high concept level may add to common sense while rules at low concept level may not be useful always.

Using uniform minimum support for all levels:

• When a uniform minimum support threshold is used, the search procedure is simplified.
• The method is also simple, in that users are required to specify only one minimum support threshold.
• The same minimum support threshold is used when mining at each level of abstraction.
• For example, in Figure, a minimum support threshold of 5% is used throughout.
• (e.g. for mining from “computer” down to “laptop computer”).
• Both “computer” and “laptop computer” are found to be frequent, while “desktop computer” is not.

Using reduced minimum support at lower levels:

• Each level of abstraction has its own minimum support threshold.
• The deeper the level of abstraction, the smaller the corresponding threshold is.
• For example in Figure, the minimum support thresholds for levels 1 and 2 are 5% and 3%, respectively.

• In this way, “computer,” “laptop computer,” and “desktop computer” are all considered frequent. Multilevel Association rule consists of alternate search strategies and Controlled level cross filtering:

• Alternate Search Strategies:

Level by level independent:

• Full breadth search.
• No background knowledge in pruning.
• Leads to examine lot of infrequent items.

Level-cross filtering by single item:

• Examine nodes at level i only if node at level (i-1) is frequent.
• Misses frequent items at lower level abstractions (due to reduced support).

Level-cross filtering by k-itemset:

• Examine k-itemsets at level i only if k-itemsets at level (i-1) is frequent.
• Misses frequent k-itemsets at lower level abstractions (due to reduced support).

Controlled Level-cross filtering by single item:

• A modified level-cross filtering by single item.
• Sets a level passage threshold for every level.
• Allows the inspection of lower abstractions even if its ancestor fails to satisfy min_sup threshold.